Smart tools for audio production have been making its way into modern audio production and is getting more popular in studio and postproduction work. In live sound however, there is few alternatives that exist. In this study live sound engineers experienced in live music sound reinforcement were interviewed about how they use gain and what considerations they make when adjusting gain. The aim of this study was to use their answers to create the foundation of a framework to an algorithm that can adjust gain automatically. The interviews were semi-structured, and the transcriptions were analysed using grounded theory. From the transcripts five categories were created and further divided into subcategories for deeper analysis. The study showed that the data in the study could not easily be proceduralized but instead two alternative ways of implementing this in practice, one that monitors the input signals and passes the information to the engineer. And another that adds a control layer to the monitoring where the parameter can be selected based on mixing strategy and the algorithms control can be switched on or off.

This study have identified and analysed anomalous meteor head echos detected by the MU Radar, as well as reproduced an interference anomaly through simulation with the use of an existing analysis pipeline. The parameters used to detect anomalies were High Start Altitude [HSAA], High Radar Cross Section [HRCSA] and High Eccentricity [HEA]. A cut-off of the head echo signal were the cause of the HSAA’s. Trail echos misclassified as head echoes and low agreement with the multiple emitter location and signal parameter estimation (MUSIC) method gave rise to the HRCSA’s. The majority of the HEA’s were given a falsely high eccentric- ity due to high beam angle and trail echos detection. Three found HEA’s showed a small possibility of having an hyperbolic orbit. Additionally, a simulation was made which concluded that signal interference will occur between two echos if the range is the same to the radar.

The cab assembly line in Oskarshamn is one of the world's most high tech production unit. With close to 300 robots the cab is assembled with merely programmed robots and no input from humans. Scania CV AB is a world leading manufacturer of trucks with high influence on the market globally.

Even though robots do most of the work, there have been human brains behind the robot execution, and there is constant work ongoing to further increase efficiency and cycle times to meet the increasing global demand for logistics services. The robots are mainly programmed offline, using the ABB software Robotstudio, which basically creates a digital representation of the actual control system without interfering with the production. Testing upgraded programs as well as simulating them offline before implementation is an essential daily operation to make the production meet the demands.

This thesis is divided into two objectives, one theoretical and one practical. The theoretical part focuses on the software, and consists of a critical analysis of a series of different software solutions for programming robots offline, as well as a look into how the offline programming processes work today in-house. The practical objective is to further improve the quality of the simulations conducted through creating tools to answer the calls from functional packages for the different processing equipment used on site. These functional packages lets you perform spot welding, gluing or gripping for instance, and as it is an outsourced service a lot of the coding is encrypted which prevents simulations being conducted with the pre-programmed routines, it makes the simulations crash.

This report presents conclusions made regarding the use of offline programming equipment both in the regards of daily operations as well as long term strategies with digital twins and digitization. It also proves that the functional packages still can be simulated even though the code has been manipulated and encrypted at one point. It holds the complete ways of how to, from a 3D CAD model, create mechanisms, synchronize external axes, and creating smart components to answer digital inputs and presenting digital outputs to the system to have a fully functional simulation run.

Purpose: The aim of this study was to describe occupational therapists’ experience of using Constraint Induced Movement Therapy for children with hemiplegic cerebral palsy. Methods: A qualitative method was chosen to describe the subjective experiences of the occupational therapists. Eight semi structured interviews were conducted with occupational therapists that were working at different centres for child and adolescent rehabilitation in this country, thereafter the collected data was analysed using qualitative content analysis. Result: The results were divided into four categories: The occupational therapist’s support, The importance of the network, Adaptation of the intervention and The organisational structures. The result indicate that the intervention should be centred on the child’s motivation and play in collaboration with the child’s social network and the intervention usually leads to an extended activity repertoire for the child. Furthermore, the result indicates the intervention to be time consuming, demanding extensive structure and resources, which led to the intervention was performed by only a few occupational therapists. It also appeared that collegial support among occupational therapists promotes the implementation of Constraint Induced Movement Therapy. Conclusion: The study show that the child’s range of activities often were improved when using Constraint Induced Movement Therapy, but this could not be proven with today’s assessment instrument.

Decentralized retail sites are facing increased challenges with retail digitalization. Another challenge is that societies are progressing towards sustainable cities. As the cities grow the decentralized retail sites are becoming a centralized part of the city. Järfälla municipality in Stockholm County, mentions in their latest comprehensive plan that Barkarby Retail Center will have an urban development scheme in 2050. The plan also states that the area will be a part in connecting the local municipality centers.

The aim of this study was to determine the possibilities of reducing car dependency in decentralized retail sites with compact development. The study resulted in an area proposal for Barkarby Retail Center, where the existing retail were adapted to an urban development with an improved accessibility and continued economic value.

Theoretical studies concluded that compact development is a working strategy to make people drive less, if it is combined with an improved public transport. The studies also concluded that even though the retail is getting more digitalized, the importance of physical stores is still proven to be important for profitability. By minimizing the retail space and implementing home delivery for bulky goods, the decentralized retail could be adapted to an urban development scheme. In order to maintain the accessibility of the area, the area’s pedestrian and bicycle networks were improved, parking spaces were gathered at the outskirts of the area and a new public transport line was drawn through the area.

The aim of the study was to explore occupational therapists experience of working with individuals diagnosed with schizophrenia in forensic psychiatric inpatient care. The authors chose a qualitative methodology and conducted eight semi-structured interviews with occupational therapists who worked in forensic psychiatry in south, middle and north of Sweden. The collected data was transcribed and analyzed according to a qualitative analysis method which resulted in four categories and four subcategories; Occupational evaluation, assessments and the use of assessment instruments with patients with schizophrenia; Impacts of factors and guidelines on evaluation work and Assessments and evidence based assessment instruments in inpatient care, Security and restriction guidelines in a structured environment; Impacts of restriction on prescribing aids and Opportunities and challenges to work in a constrained environment, Opportunities to work with activity and skills with patients with schizophrenia and Work with motivation, initiative and activity to increase participation. The result showed occupational therapists' experience of working in an environment adapted to safety and restrictions with individuals diagnosed with schizophrenia. The study shows the importance of occupational therapy competence in working with patients who have been diagnosed with schizophrenia to enable participation and independence despite the impact of the environment. More research is required on how occupational therapeutic skills and assessment tools should be adapted to a structured and controlled environment to enable more quality-assured rehabilitative care for patients who have schizophrenia in forensic psychiatric care.

This article proposes a Deep Learning (dl) method to enable fully autonomous flights for low-cost Micro Aerial Vehicles (MAVs) in unknown dark underground mine tunnels. This kind of environments pose multiple challenges including lack of illumination, narrow passages, wind gusts and dust. The proposed method does not require accurate pose estimation and considers the flying platform as a floating object. The Convolutional Neural Network (CNN) supervised image classifier method corrects the heading of the MAV towards the center of the mine tunnel by processing the image frames from a single on-board camera, while the platform navigates at constant altitude and desired velocity references. Moreover, the output of the CNN module can be used from the operator as means of collision prediction information. The efficiency of the proposed method has been successfully experimentally evaluated in multiple field trials in an underground mine in Sweden, demonstrating the capability of the proposed method in different areas and illumination levels.

The usage of Micro Aerial Vehicles (MAVs) in different applications is gaining attention, however one of the main challenges is to provide collision free paths, despite the uncertainties in localization, mapping, or path planning. This article proposes a novel collision-free path planner for MAV navigation in confined environments, while not being dependent on the information of the localization, only relying on 2D local point-cloud data. The proposed backup path planner generates velocity commands for a trajectory-following controller, while guaranteeing a safety distance from all points in the local-point-cloud. The proposed method considers the kinematics of the MAV and can be extended to any robotics application, such as ground vehicles. The proposed method is evaluated in a Gazebo simulation environment and successfully provides a collision-free navigation.

High-strength concrete (HSC) is highly applicable to the construction of heavy structures. However, shear strength (Ss) determination of HSC is a crucial concern for structure designers and decision makers. The current research proposes the novel models based on the combination of adaptive neuro-fuzzy inference system (ANFIS) with several meta-heuristic optimization algorithms, including ant colony optimizer (ACO), differential evolution (DE), genetic algorithm (GA), and particle swarm optimization (PSO), to predict the Ss of HSC slender beam. The proposed models were constructed using several input combinations incorporating several related dimensional parameters such as effective depth of beam (d), shear span (a), maximum size of aggregate (ag), compressive strength of concrete (fc), and percentage of tension reinforcement (ρ). To assess the impact of the non-homogeneity of the dataset on the prediction result accuracy, two possible modeling scenarios, (i) non-processed (initial) dataset (NP) and (ii) pre-processed dataset (PP), are inspected by several performance indices. The modeling results demonstrated that ANFIS-PSO hybrid model attained the best prediction accuracy over the other models and for the pre-processed input parameters. Several uncertainty analyses were examined (i.e., model, variables, and data), and results indicated predicting the HSC shear strength was more sensitive to the model structure uncertainty than the input parameters.

Agricultural land in the south of Iraq provides habitat for several types of living creatures. This land has a significant impact on the ecosystem. The agricultural land of Al-Hawizeh marsh covers an area of more than 3500 km2 and is considered an enriched resource to produce several harvests. A total of 74% of this area suffers from a high degree of salinity and chemical pollution, which needs to be remedied. Several human-made activities and post-war-related events have caused radical deterioration in soil quality in the agricultural land. The goal of this research was to integrate mathematical models, remote sensing data, and GIS to provide a powerful tool to predict, assess, monitor, manage, and map the salinity and chemical parameters of iron (Fe), lead (Pb), copper (Cu), chromium (Cr), and zinc (Zn) in the soils of agricultural land in Al-Hawizeh marsh in southern Iraq during the four seasons of 2017. The mathematical model consists of four parts. The first depends on the B6 and B11 bands of Landsat-8, to calculate the soil moisture index (SMI). The second is the salinity equation (SE), which depends on the SMI result to retrieve the salinity values from Landsat-8 images. The third part depends on the B6 and B7 bands of Landsat-8, which calculates the clay chemical index (CCIs). The fourth part is the chemical equation (CE), which depends on the CCI to retrieve the chemical values (Fe, Pb, Cu, Cr, and Zn) from Landsat-8 images. The average salinity concentrations during autumn, summer, spring, and winter were 1175, 1010, 1105, and 1789 mg/dm3, respectively. The average Fe concentrations during autumn, summer, spring and winter were 813, 784, 842, and 1106 mg/dm3, respectively. The average Pb concentrations during autumn, summer, spring, and winter were 4.85, 3.79, 4.74, and 7.2 mg/dm3, respectively. The average Cu concentrations during autumn, summer, spring, and winter were 3.9, 3.1, 4.45, and 7.5 mg/dm3, respectively. The average Cr concentrations during autumn, summer, spring, and winter seasons were 1.28, 0.73, 1.03, and 2.91 mg/dm3, respectively. Finally, the average Zn concentrations during autumn, summer, spring, and winter were 8.25, 6, 7.05, and 12 mg/dm3, respectively. The results show that the concentrations of salinity and chemicals decreased in the summer and increased in the winter. The decision tree (DT) classification depended on the output results for salinity and chemicals for both SE and CE equations. This classification refers to all the parameters simultaneously in one stage. The output of DT classification results can display all the soil quality parameters (salinity, Fe, Pb, Cu, Cr, and Zn) in one image. This approach was repeated for each season in this study. In conclusion, the developed systematic and generic approach may constitute a basis for determining soil quality parameters in agricultural land worldwide.

Outotec Sweden AB works in the field of precious metal refining. Silver electrorefining is one of Outotec’s technologies widely applied in numerous silver refining plants worldwide. During this project a specific section in a silver refinery plant has been investigated. Today’s system provided by Outotec utilises gravity as a means of transport of the slurry consisting of refined silver crystals and silver electrolyte. The slurry is directed from the electrolysis cells through pipes mounted in an angle towards a separation tank. This solution requires three floors of the building of the refinery plant. The goal of this project was to develop concepts which would transport the slurry of silver crystals from the electrolysis cells to a separation tank within a single floor of the building. The implementation of such a system would result in lowering the overall investment cost of the refinery by at least 7 %.

Ulrich & Eppinger’s product development process has been utilised in this thesis work which is a six step sequential method for development of products. Through this process, four concepts for transportation of silver crystal slurry were developed, analysed and cost estimated - Syringe, Drop to circulation tank, Suction Pump and Conveyor. The syringe concept eliminated the need for a single floor of the refinery, which translated to total projected investment cost of 337 000 SEK and an overall investment savings of 8.3 %. Drop to circulation tank eliminated the need for two floors which lead to a total estimated cost of 862 000 SEK. This corresponded to an overall investment savings of 16.5 %. The two final concepts - suction pump and conveyor was estimated to cost 346 000 and 337 000 SEK respectively. Both of the concepts resulted in a total projected savings of the overall investment by 8.3%, eliminating the need for one of the three floors in the refinery. The conclusion is that each of the concepts developed surpassed the goal of lowering the overall investment of the refinery by at least 7%. Three of the four concepts eliminated the need for one floor while the final one, drop to circulation tank, eliminated the need for two of the three floors.

The concepts must be tested before implemented. This could either be conducted by approximating the electrolyte as water and silver crystals as metal shavings or by sludge. It would however be beneficial if a test rig is constructed for each concept and they are tested with the same mixture of silver slurry that is transported in Outotec’s existing refineries.

The circulation tank should also be installed on the same floor as the electrolysis cells and the separation tank for the syringe, conveyor and suction pump concepts. This was never investigated by the authors since it was a limitation stated as the project was initiated. This component was however included in the drop to circulation tank concept since it was considered being part of the transportation system. If the circulation tank is installed on the same floor as the other components it will result in eliminating the need for two floors, which would ultimately lead to a substantial decrease in overall investment cost.

In a coastal environment, this paper investigated the formation process and the cumulative shape of subaqueous mounds formed by hopper dredged discharges. Hydrological observations and field tests were performed to examine the flow features and ultimately generated morphology characteristics. A high-precision digital elevation model (DEM) was established by multi-beam depth sweeping (MBDS) in the experiment. Particular attention was paid to the formation of the mounds, the three-dimensional shape and the influence factors. The field measurements showed that the mounds were roughly symmetrical in space, and the tidal current, though of weak strength, played a certain role in shaping the profiles. Cone and volcanic cone mound tops were observed, featuring the main top shapes. The height and covered area of the mounds were proportional to the amount of dumped sediment, and they were also affected a lot by the water depth. The results of superimposed tests showed that the second placement over the existing mound resulted in a similar overall shape, but there was pronounced movement around the mound; additional discharged volumes at the same location mainly increased the mound height. The field tests provided a reference for understanding the sediment dumping in other similar coastal areas.

The check dams in grassed stormwater channels enhance infiltration capacity by temporarily blocking water flow. However, the design properties of check dams, such as their height and spacing, have a significant influence on the flow regime in grassed stormwater channels and thus channel infiltration capacity. In this study, a mass-balance method was applied to a grassed channel model to investigate the effects of height and spacing of check dams on channel infiltration capacity. Moreover, an empirical infiltration model was derived by improving the modified Kostiakov model for reliable estimation of infiltration capacity of a grassed stormwater channel due to check dams from four hydraulic parameters of channels, namely, the water level, channel base width, channel side slope, and flow velocity. The result revealed that channel infiltration was increased from 12% to 20% with the increase of check dam height from 10 to 20 cm. However, the infiltration was found to decrease from 20% to 19% when a 20 cm height check dam spacing was increased from 10 to 30 m. These results indicate the effectiveness of increasing height of check dams for maximizing the infiltration capacity of grassed stormwater channels and reduction of runoff volume.

Considering the scouring depth downstream of weirs is a challenging issue due to its effect on weir stability. The adaptive neuro-fuzzy inference systems (ANFIS) model integrated with optimization methods namely cultural algorithm, biogeography based optimization (BBO), invasive weed optimization (IWO) and teaching learning based optimization (TLBO) are proposed to predict the maximum depth of scouring based on the different input combinations. Several performance indices and graphical evaluators are employed to estimate the prediction accuracy in the training and testing phase. Results show that the ANFIS-IWO offers the highest prediction performance (RMSE = 0.148) compared to other models in the testing phase, while the ANFIS-BBO (RMSE = 0.411)ANFIS-TLBO-M3 RMSEtesting=0.411, CCtesting~0.00) provides the lowest accuracy. The findings obtained from the uncertainty analysis of prediction modeling indicate that the input variables variability R-factor=1.72has a higher impact on the predicted results than the structure of models. In general, the ANFIS-IWO can be used as a reliable and cost-effective method for predicting the scouring depth downstream of weirs.

Development of landslide predictive models with strong prediction power has become a major focus of many researchers. This study describes the first application of the Hyperpipes (HP) algorithm for the development of the five novel ensemble models that combine the HP algorithm and the AdaBoost (AB), Bagging (B), Dagging, Decorate, and Real AdaBoost (RAB) ensemble techniques for mapping the spatial variability of landslide susceptibility in the Nam Dan commune, Ha Giang province, Vietnam. Information on 76 historical landslides and ten geo-environmental factors (slope degree, slope aspect, elevation, topographic wetness index, curvature, weathering crust, geology, river density, fault density, and distance from roads) were used for the construction of the training and validation datasets that are the prerequisites for building and testing the proposed models. Using different performance metrics (i.e., the area under the receiver operating characteristic curve (AUC), negative predictive value, positive predictive value, accuracy, sensitivity, specificity, root mean square error, and Kappa), we verified the proficiency of all five ensemble learning techniques in increasing the fitness and predictive powers of the base HP model. Based on the AUC values derived from the models, the ensemble ABHP model that yielded an AUC value of 0.922 was identified as the most efficient model for mapping the landslide susceptibility in the Nam Dan commune, followed by RABHP (AUC = 0.919), BHP (AUC = 0.909), Dagging-HP (AUC = 0.897), Decorate-HP (AUC = 0.865), and the single HP model (AUC = 0.856), respectively. The novel ensemble models proposed for the Nam Dan commune and the resultant susceptibility maps can aid land-use planners in the development of efficient mitigation strategies in response to destructive landslides.

Many of today’s engineering advancements rely on minerals such as copper, gold and iron. For this reason, the mining industry plays an important role for the development of society and technological wonders. Mining excavators are commonly used tools for extracting the minerals from the mine. Mining excavators are large machines used to breakdown, penetrate and load the rock ores onto trucks that transport the minerals. During the dynamic loading, the excavator bucket experiences significant amount of wear and tear that negatively affects the production by increasing the downtime. The bucket teeth are arguably the most worn parts of the bucket and are responsible for significant amounts of downtime. This thesis aims to provide a better understanding of the load and wear on the bucket teeth of large scale mining excavators used in Bolidens Aitik copper mine in Sweden. Because of how much wear and tear the bucket teeth are exposed to, there is a need to better understand the wear behaviour of the teeth and for the whole bucket in general. This understanding can then be used to improve the service life of the teeth and other parts of the bucket and thus increase work efficiency and reduce downtime.

This project was divided into two parts. The first part consisted of regular field measurements to follow the wear on the bucket for about two weeks of digging and loading. The gathered data was then analysed to provide a better understand about the wear behaviour. The second part was to develop a numerical model that could predict the wear on the bucket and could be verified by the field measurements.

The field measurements consisted of seven 3D laser scans of the bucket starting with brand new teeth. At the time of the last scan, the buckets total loaded tonnage was approximately 542 kton and the excavator had operated in total of approximately 195 hours. After the raw data from the scans was gathered and analysed, various information about the wear behaviour on the teeth was achieved. The 3D scanned data was also used to provide a complete wear development cycle which allowed to track the wear of any point in the bucket. The method could also be used to create animations of the teeth as they were being worn. From the results, it was concluded that the wear rate for the teeth slowed down and even converged as the geometry changed due to wear. When comparing all nine teeth on the bucket, it was also found that the middle teeth on the bucket were most exposed to wear. The most worn tooth was found to lose around 50 kg of weight after approximately 117 operating hours, which accounts for 40 % of the original weight. The animations from the complete wear development results also showed how the individual teeth and the whole leading edge with all nine teeth were being worn as the buckets loaded tonnage increased from 0 to 542 kton.

The numerical model consisted of simulations of loading with the rocks being modelled with the Discrete Element Method (DEM). These were divided into four cases, the first being with the bucket with all new teeth. The second bucket with a mixture of new and worn teeth. The third bucket with all worn teeth and then finally the fourth bucket in which a new tooth geometry was tested. The numerical model showed promising results and potential for being a reliable way to predict the wear on the bucket. The results showed that both the penetration force and wear for the middle teeth was higher than the other neighbouring teeth. It also showed that the completely worn teeth had a lower wear rate than the new teeth which is in agreement with the results from field measurements. Other factors such as tooth shape and length were also observed to have a significant impact on the wear and penetration force. Lastly, the new teeth geometry also showed potential for design improvements in terms of wear resistance but can be further optimised. From the new teeth geometry, a suggestion was given for using an existing tooth system that might be more wear resistant.

Appropriate input selection for the estimation matrix is essential when modeling non-linear progression. In this study, the feasibility of the Gamma test (GT) was investigated to extract the optimal input combination as the primary modeling step for estimating monthly pan evaporation (EPm). A new artificial intelligent (AI) model called the co-active neuro-fuzzy inference system (CANFIS) was developed for monthly EPm estimation at Pantnagar station (located in Uttarakhand State) and Nagina station (located in Uttar Pradesh State), India. The proposed AI model was trained and tested using different percentages of data points in scenarios one to four. The estimates yielded by the CANFIS model were validated against several well-established predictive AI (multilayer perceptron neural network (MLPNN) and multiple linear regression (MLR)) and empirical (Penman model (PM)) models. Multiple statistical metrics (normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (NSE), Pearson correlation coefficient (PCC), Willmott index (WI), and relative error (RE)) and graphical interpretation (time variation plot, scatter plot, relative error plot, and Taylor diagram) were performed for the modeling evaluation. The results of appraisal showed that the CANFIS-1 model with six input variables provided better NRMSE (0.1364, 0.0904, 0.0947, and 0.0898), NSE (0.9439, 0.9736, 0.9703, and 0.9799), PCC (0.9790, 0.9872, 0.9877, and 0.9922), and WI (0.9860, 0.9934, 0.9927, and 0.9949) values for Pantnagar station, and NRMSE (0.1543, 0.1719, 0.2067, and 0.1356), NSE (0.9150, 0.8962, 0.8382, and 0.9453), PCC (0.9643, 0.9649, 0.9473, and 0.9762), and WI (0.9794, 0.9761, 0.9632, and 0.9853) values for Nagina stations in all applied modeling scenarios for estimating the monthly EPm. This study also confirmed the supremacy of the proposed integrated GT-CANFIS model under four different scenarios in estimating monthly EPm. The results of the current application demonstrated a reliable modeling methodology for water resource management and sustainability.

The effectiveness of a flat-plate solar collector was studied by using SiO2, Al2O3, Graphene, and graphene nanoplatelets nanofluids with distilled water as the working fluids. The energy efficiency was theoretically compared using MATLAB programming. The prepared carbon and metallic oxides nanomaterials were structurally and morphologically characterized via field emission scanning electron microscope. The study was conducted under different operating conditions such as different volume fractions (0.25%, 0.5%, 0.75% and 1%), fluid mass flow rate (0.0085, 0.017, and 0.0255 kg/s), input temperatures (30, 40, and 50 °C), and solar irradiance (500, 750, and 1000 W/m2). Nanofluids showed better thermophysical properties compared to standard working fluids. With the addition of the nanofluids SiO2, Al2O3, Gr and GNPs to the FPSC the highest efficiency of 64.45%, 67.03%, 72.45%, and 76.56% respectively was reached. The results suggested that nanofluids made from carbon nanostructures and metallic oxides can be used in solar collectors to increase the parameters of heat absorbed/loss compared to water only usage.

More and more people commute to work, travel and use the electric bicycle as a daily means of transport. The need for bicycle racks, adapted for electric bicycles is growing and the demands on bicycle racks are higher than for bicycle racks for ordinary bicycles. This as they are very expensive to buy. On behalf of NOLA Industries, a bicycle rack for electric bicycles will be designed. The bicycle rack must also meet the need to recharge the batteries while the bicycle is parked and meet all found requirements from all stakeholders, which were collected during the project. The project is carried out by one student from Luleå University of Technology, who is studying M.Sc. in industrial design with a focus on product development. The project was carried out in Luleå with NOLA at a distance in Stockholm. The aim of the project was to come up with an idea for a bicycle rack that is suitable for public environments and that also fits into NOLA’s existing product range. At the beginning of the project, the time was planned using a Gantt scheme. The process used was CDIO consisting of four different phases. After the planning was completed, a benchmarking was made of how the situation looked and how the electric bicycles in today’s society work. The theory section was planned and introduced with a description of the line of technical design. The chapter was then followed up with relevant theory for the project. In order to find out what users think of existing bicycle racks and what were the desires for future bicycle racks, a survey was sent out. The work continued with several different information collection methods which were then followed up with creative work in the design phase. The final work included CAD models and renderings from keyshot of the finished concept. The final concept meets stakeholder requirements for an electric bike rack. It fulfill the need to be able to recharge the electric bike’s battery and to lock the electric bike in several points. The roof and the bicycle racks are equipped with led lighting, counteracting vandalism and theft of the electric bicycles. The roof also protects the electric bicycles against weather conditions.

By analyzing the same Bell experiment in different reference frames, we show that nature at its fundamental level is superdeterministic, not random, in contrast to what is indicated by orthodox quantum mechanics. Events—including the results of quantum mechanical measurements—in global space-time are fixed prior to measurement.

Sewer pipe networks are expected to operate with minimal or no interruptions. The complex nature of randomlyoccurring failures in sewer networks arising from blockages significantly adds to the cost of operation and maintenance.Blockages are significant due to sewage backup or basements flooding, resulting from theiroccurrence. Therefore, continuous performance assessment of sewer pipe networks is necessary to ensurerequired levels of service at an acceptable cost. This study provides insight into the performance of the sewerpipe networks by assessing the proneness of the network to blockages. Furthermore it draws inferences at a holisticstrategic level of influential explanatory factors of blockage proneness, using data available in the SwedishWater and Wastewater Association’s benchmarking system. Results indicate that medium sized municipalitiesare prone to at least 30% more blockages per km per year compared to other municipalities. A hypothesis ofexplanatory factors includes reduced flow volumes and flow depth. Flow velocities below self-cleaning velocityin sewer pipe networks, encouraged by sluggishness of flow are responsible for increased possibility for sedimentdeposition and accumulation in sewers leading to blockages. This is also exacerbated by the deposition of nondisposables(wet wipes, baby diapers, hard paper, etc.), accumulation of fats, oils and grease in sewers andincreased water conservation measures.

Mosul Dam is an earth fill dam, with a storage capacity of 11.11 km3 constructed on highly karstified gypsum beds alternating with marl and limestone. After impounding in 1986, seepage locations were recognized. The dam situation now indicates that it is in a state of extreme relative risk. If it fails, then 6 million people will be affected and 7202 km2 area will be flooded. Grouting operations will elongate the life of the dam but will not solve the problem. Building a protection dam downstream will be the best measures to secure the safety of the downstream area and its’ population.

The effects of distortion has been investigated prior to this study, however most of these studies focus on the objective physicalities of a certain type of distortion or they might apply distortion in static amounts to examine effects of loudspeaker distortion. Objectively the varying types of distortion may be different, however there are little explanations on how these types subjectively might sound different. This study aimed to investigate how subjective preference and perception of the timbral attributes warmth and roughness may vary between types of distortion, and if there was a pattern between these using three different types of distortion (zero-crossing, solid state and tube), applied at two different levels (high and low) and to two different instruments (guitar and vocals). The outcome indicated that subjects most prefer tube distortion and that this distortion was considered to provide the most amounts of warmth while also the least amounts of roughness. There were also interaction effects indicating guitar being less sensitive about the level of distortion while being more sensitive about the type of distortion for the measures of preference and amounts of roughness, when compared to vocals.

In live sound reinforcements scenarios, the majority of the audience is placed in a non- optimal listening position and will not experience the stereophonic image as intended by the mixing engineer. This study was conducted to examine the impact of a central loudspeaker source and phantom center, on the stereophonic image from different listening positions. Sixteen subjects, consisting of audio engineering students and professionals, were subjected to an optimal and non-optimal listening position and a three channel and stereo system, and was asked to estimate the perceived location of a stimulus, consisting of a 40 ms 1 kHz tone, placed on five different locations within the panorama. The results of these test were then summarized and analyzed by utilizing three t-tests in order to examine; the difference between perceived and intended location for each combination of system configuration and listening position, the difference between the listening positions and the difference between system configurations. The results show that a three-channel system is less affected by the listening position than a stereo system, indicating that a three-channel system can provide a more similar experience to audience members regardless of their listening position. However, the preference of system configuration is not examined and should be examined before making the claim that one system configuration is superior. The number of t-test conducted may also have impacted the results and provided a false significance. Subsequent studies could be made to confirm or reject the results of this study.